This paper presents a vision-based real-time driver fatigue detection system for driving safety. Based on skin colors, the driver's face is located from a color video captured in a car. Then, edge detection is employed to locate the regions of the driver's eyes, which are used as the templates for eye tracking in subsequent frames. Finally, the tracked eyes' images are used for fatigue detection in order to generate warning alarms for driving safety. The proposed system was tested on a Pentium M 1.4G notebook with 512 MBRAM. The experimental results seemed quite encouraging and promising. The system could reach more than 30 frames per second for eye tracking, and the average correct rate for eye location and tracking could achieve 96.0% on five test videos. Though the average precision rate of fatigue detection was 89.3%, the correct detection rate could achieve 100% on the test videos.
Relation:
淡江理工學刊=Tamkang Journal of Science and Engineering 11(1), pp.65-72
